CN116260470A - Adaptive LDPC iterative decoding method and device - Google Patents
Adaptive LDPC iterative decoding method and device Download PDFInfo
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- H03M13/05—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words using block codes, i.e. a predetermined number of check bits joined to a predetermined number of information bits
- H03M13/11—Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words using block codes, i.e. a predetermined number of check bits joined to a predetermined number of information bits using multiple parity bits
- H03M13/1102—Codes on graphs and decoding on graphs, e.g. low-density parity check [LDPC] codes
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- H03M13/1128—Judging correct decoding and iterative stopping criteria other than syndrome check and upper limit for decoding iterations
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Abstract
The application relates to a self-adaptive LDPC iterative decoding method and a device, wherein the method comprises the following steps: and combining the decoding result of the previous round of iterative decoding and the channel input of the previous round of iterative decoding, correcting the channel input of the current round of iterative decoding to obtain corrected coded bit soft information so as to obtain coded bit average mutual information of the current round of prediction, predicting the decoding result under different complexity decoding modes, determining corresponding decoding options, outputting corresponding decoding option control signals, and performing iterative decoding on the corrected coded bit soft information under the corresponding decoding modes to obtain a final decoding result. Therefore, the method solves the technical problems that in the related technology, the decoding performance of a plurality of decoding modes is difficult to accurately predict, the prediction result is influenced, the comprehensive performance of the decoding mode is poor, the performance of the selectable decoding mode is greatly limited, the effective correction of channel parameter estimation errors is lacking, the actual decoding performance is reduced, the decoding efficiency is reduced and the like.
Description
Technical Field
The present disclosure relates to the field of digital information transmission technologies, and in particular, to a method and an apparatus for adaptive LDPC iterative decoding.
Background
The LDPC (Low-Density Parity-Check Code) Code is a linear block Code with sparse characteristics of a Check matrix, and because the LDPC Code has advantages of excellent threshold performance, linear relation between decoding complexity and Code length, flexible configuration of decoding parallelism and the like, the LDPC Code is widely applied in the channel coding field of a digital communication system, for example, a 5G novel air interface and a wireless local area network IEEE 802.11 series standard in the communication field, a DVB-S2/T2/C2/NGH standard in the broadcasting field, a DTMB/DTMBA standard, an ATSC3.0 standard and the like.
The common decoding algorithm of the LDPC code is a soft information message transfer iterative decoding algorithm, wherein the SPA (Sum-Product Algorithm) algorithm has good threshold performance, but the row operation unit of the LDPC code relates to special operations such as tanh and the like, has high calculation complexity and is sensitive to channel parameter estimation errors; the MSA (Min-Sum Algorithm) Algorithm replaces tanh and other operations with Min operation, has low computational complexity, is robust to channel parameter estimation errors, but has poor threshold performance. In the related art, an AQNMSA (Adaptive Quantized and Normalized MSA, adaptive quantization and adaptive normalization minimum sum LDPC decoding algorithm) algorithm is also proposed, so that low computational complexity and excellent robust characteristics of MSA are well maintained, and meanwhile, the decoding threshold performance of the conventional MSA is improved, but the decoding threshold performance of the conventional MSA is still a certain difference from the SPA.
The LDPC iterative decoder in the related art generally adopts a fixed decoding mode for decoding, so that the decoding performance, the decoding efficiency and the throughput rate of the decoder under different channel qualities and different decoding algorithms cannot be considered.
The related art decoding performance prediction method predicts decoding performance using channel parameters, i.e., SNR (Signal-to-Noise Ratio), and CSI (Channel State Information ), the prediction error of which is large. AMI (Average Mutual Information ) of the encoded bit soft information can be calculated by using the encoded bit soft information input by the LDPC iterative decoder, i.e., the channel input. There is a close relationship between the accurate AMI of the coded Bit soft information and the BER (Bit Error Rate) or BLER (Block Error Rate) performance result in a specific decoding mode given the decoding mode. Therefore, BER or BLER performance results for a particular coding mode can be better predicted with accurate AMI. Meanwhile, when the code bit soft information input by the channel is inaccurate, the calculated AMI also generates errors, and further the accuracy of the decoding performance prediction is affected.
The channel parameter estimation error can directly cause the linear scale change of the code bit soft information input by the channel, and meanwhile, the non-optimal constellation demapping algorithm or detection algorithm can also influence the scale change of the code bit soft information input by the channel. Therefore, when there is a channel parameter estimation error, it is necessary to linearly correct the coded bit soft information inputted from the channel. The forward correction method in the related art uses the preset LDPC iterative decoder operating point information to directly calculate the soft information of the code bits input by the channel to obtain the LLR (Log Likelihood Ratio ) correction parameters, and has high calculation complexity, and the reliability of the correction result cannot be ensured because the consistency of the actual operating point and the preset operating point cannot be ensured.
In summary, in the related art, the LDPC iterative decoding method has the following disadvantages, and needs to be improved:
1. a prediction method capable of accurately predicting the decoding performance of a plurality of decoding modes is lacking: the decoding performance prediction method in the related art predicts the decoding performance by using the SNR and the CSI, and the prediction error is larger;
2. lack of better-comprehensive-performance decoding modes: the optional decoding mode of the adaptive LDPC iterative decoding method in the related art is usually MSA or other decoding modes with poor decoding performance, so that the adaptive LDPC iterative decoding method is limited by the performance of the optional decoding mode and has poor decoding performance;
3. lack of effective correction means for channel parameter estimation errors: the forward correction method in the related art has high computational complexity, and the working point information of the LDPC iterative decoder needs to be preset, so that the reliability of the correction result cannot be ensured.
Disclosure of Invention
The application provides a self-adaptive LDPC iterative decoding method and device, which are used for solving the technical problems that in the related art, the decoding performance of a plurality of decoding modes is difficult to accurately predict, the prediction result is influenced, the comprehensive performance of the decoding mode is poor, the limitation of the performance of an optional decoding mode is larger, and the effective correction of channel parameter estimation errors is lacking, so that the actual decoding performance is reduced, the decoding efficiency is reduced and the like.
An embodiment of a first aspect of the present application provides an adaptive LDPC iterative decoding method applied to a low density parity check code iterative decoder, where the method includes the following steps: receiving channel input of current round iterative decoding, and correcting the channel input of the current round iterative decoding by combining a decoding result of the previous round iterative decoding and the channel input of the previous round iterative decoding to obtain corrected coded bit soft information; obtaining coding bit average mutual information of current round prediction based on the corrected coding bit soft information, predicting decoding results under different complexity decoding modes based on the coding bit average mutual information of the current round prediction, determining corresponding decoding options, and outputting corresponding decoding option control signals; and selecting a corresponding decoding mode according to the decoding option control signal, so as to perform iterative decoding on the corrected coded bit soft information under the corresponding decoding mode, and obtaining a final decoding result.
Optionally, in one embodiment of the present application, before receiving the channel input of the current round of iterative decoding, the method further includes: initializing a log-likelihood ratio correction parameter, a working point of the low-density parity-check code iterative decoder and a loop self-adaptive correction parameter.
Optionally, in an embodiment of the present application, said modifying the channel input of the current round of iterative decoding includes: adjusting the log likelihood ratio correction parameters by using a preset forward correction method or a loop correction method; and correcting the channel input of the current round of iterative decoding by using the log-likelihood ratio correction parameters to obtain the corrected coded bit soft information.
Optionally, in an embodiment of the present application, the adjusting the log likelihood ratio correction parameter by using a forward correction method includes: and calculating the log likelihood ratio correction parameter of the current round iteration by using the working point of the low-density parity check code iterative decoder and combining the channel input of the current round iterative decoding.
Optionally, in an embodiment of the present application, the adjusting the log likelihood ratio correction parameter by using a loop correction method includes: combining the decoding result of the previous iteration decoding and the channel input of the previous iteration decoding, and calculating to obtain the average mutual information of the coded bits after the previous iteration correction; and calculating a difference value between the coded bit average mutual information corrected in the previous round and the coded bit average mutual information predicted in the previous round, and adjusting the log likelihood ratio correction parameter by combining the difference value and the loop self-adaptive correction parameter.
Optionally, in an embodiment of the present application, the predicting the decoding result of the different complexity decoding modes based on the coded bit average mutual information of the current round prediction and determining the decoding options includes: combining the average mutual information of the coding bits of the current round prediction with the error bit rate or the error block rate performance curve of the coding bit average mutual information under different complexity decoding modes to obtain the error bit rate or the error block rate performance prediction result of the different complexity decoding modes under the average mutual information of the coding bits of the current round prediction; and screening a decoding mode which meets a preset performance condition and has the lowest decoding complexity from the decoding modes with different complexity based on the bit error rate or block error rate performance prediction result to serve as a determined decoding option, and selecting non-decoding as the determined decoding option when all the decoding modes do not meet the preset performance condition.
An embodiment of a second aspect of the present application provides an adaptive LDPC iterative decoding apparatus applied to a low density parity check code iterative decoder, where the apparatus includes: the initialization module is used for initializing the log-likelihood ratio correction parameters, the working points of the low-density parity check code iterative decoder and the loop self-adaptive correction parameters; the correction module is used for receiving the channel input of the current round of iterative decoding, and correcting the channel input of the current round of iterative decoding by combining the decoding result of the previous round of iterative decoding and the channel input of the previous round of iterative decoding to obtain corrected code bit soft information; the prediction module is used for obtaining the coding bit average mutual information of the current round prediction based on the corrected coding bit soft information, predicting the decoding results of the current round prediction in different complexity decoding modes based on the coding bit average mutual information of the current round prediction, determining corresponding decoding options and outputting corresponding decoding option control signals; and the decoding module is used for selecting a corresponding decoding mode according to the decoding option control signal so as to carry out iterative decoding on the corrected coded bit soft information under the corresponding decoding mode to obtain a final decoding result.
Optionally, in one embodiment of the present application, the correction module includes: the adjusting unit is used for adjusting the log likelihood ratio correction parameters by using a preset forward correction method or a loop correction method; and the correction unit is used for correcting the channel input of the current round of iterative decoding by utilizing the log-likelihood ratio correction parameter to obtain the corrected code bit soft information.
Optionally, in one embodiment of the present application, the adjusting unit includes: and the first adjusting subunit is used for calculating the log likelihood ratio correction parameter of the current round iteration by utilizing the working point of the low-density parity check code iterative decoder and combining the channel input of the current round iterative decoding.
Optionally, in one embodiment of the present application, the adjusting unit further includes: a calculating subunit, configured to combine the decoding result of the previous iteration decoding with the channel input of the previous iteration decoding, and calculate to obtain the average mutual information of the coded bits after the previous iteration correction; and the second adjusting subunit is used for calculating the difference value between the coded bit average mutual information after the last round of correction and the coded bit average mutual information predicted by the last round of correction, and adjusting the log likelihood ratio correction parameter by combining the difference value and the loop self-adaptive correction parameter.
Optionally, in one embodiment of the present application, the prediction module includes: the prediction unit is used for combining the coding bit average mutual information of the current round prediction and the coding bit average mutual information-bit error rate or block error rate performance curve under different complexity decoding modes to obtain a bit error rate or block error rate performance prediction result of the different complexity decoding modes under the coding bit average mutual information of the current round prediction; and the screening unit is used for screening a decoding mode which meets a preset performance condition and has the lowest decoding complexity from the decoding modes with different complexity based on the bit error rate or block error rate performance prediction result to serve as a determined decoding option, and selecting non-decoding as the determined decoding option when all the decoding modes do not meet the preset performance condition.
An embodiment of a third aspect of the present application provides an electronic device, including: the system comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to realize the adaptive LDPC iterative decoding method according to the embodiment.
An embodiment of a fourth aspect of the present application provides a computer readable storage medium storing a computer program which, when executed by a processor, implements an adaptive LDPC iterative decoding method as above.
According to the embodiment of the application, the decoding result of the previous round of iterative decoding and the channel input of the previous round of iterative decoding can be combined, the channel input of the current round of iterative decoding is corrected, corrected coding bit soft information is obtained, accurate prediction of decoding performance results of different complexity decoding modes can be achieved, decoding options are adaptively selected, coding bit average mutual information of the current round of prediction is obtained through the corrected coding bit soft information, accordingly, decoding results in different complexity decoding modes are predicted, corresponding decoding options are determined, corresponding decoding option control signals are output, further, the corrected coding bit soft information is subjected to iterative decoding in the corresponding decoding modes, and final decoding results are obtained, so that decoding complexity and throughput rate of a decoder in different channel qualities can be considered, adaptability of the decoder to channel quality changes is enhanced, meanwhile, decoding resource waste caused by decoding failure is reduced, and decoding efficiency is improved, and accuracy and reliability of decoding results are guaranteed. Therefore, the technical problems that in the related art, the decoding performance of a plurality of decoding modes is difficult to accurately predict, the prediction result is influenced, the comprehensive performance of the decoding modes is poor, the performance of the selectable decoding modes is greatly limited, the effective correction of channel parameter estimation errors is lacking, the actual decoding performance is reduced, the decoding efficiency is reduced and the like are solved.
Additional aspects and advantages of the application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:
FIG. 1 is a flowchart of an adaptive LDPC iterative decoding method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an adaptive LDPC iterative decoding method according to an embodiment of the present application;
FIG. 3 is a flow chart of an adaptive LDPC iterative decoding method according to one embodiment of the present application;
FIG. 4 is a schematic diagram of an adaptive LDPC iterative decoding method according to another embodiment of the present application;
FIG. 5 is a flow chart of an adaptive LDPC iterative decoding method according to another embodiment of the present application;
fig. 6 is a schematic structural diagram of an adaptive LDPC iterative decoding apparatus according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present application and are not to be construed as limiting the present application.
The following describes an adaptive LDPC iterative decoding method and apparatus according to an embodiment of the present application with reference to the accompanying drawings. Aiming at the technical problems that in the related technology mentioned in the background technology center, the decoding performance of a plurality of decoding modes is difficult to accurately predict, the prediction result is influenced, the comprehensive performance of the decoding modes is poor, the limitation of the performance of the selectable decoding modes is larger, and effective correction of channel parameter estimation errors is lacking, so that the actual decoding performance is reduced, the decoding efficiency is reduced and the like. Therefore, the technical problems that in the related art, the decoding performance of a plurality of decoding modes is difficult to accurately predict, the prediction result is influenced, the comprehensive performance of the decoding modes is poor, the performance of the selectable decoding modes is greatly limited, the effective correction of channel parameter estimation errors is lacking, the actual decoding performance is reduced, the decoding efficiency is reduced and the like are solved.
Specifically, fig. 1 is a schematic flow chart of an adaptive LDPC iterative decoding method according to an embodiment of the present application.
As shown in fig. 1, the adaptive LDPC iterative decoding method is applied to a low-density parity-check code iterative decoder, wherein the method comprises the following steps:
in step S101, a channel input of the current round of iterative decoding is received, and the channel input of the current round of iterative decoding is corrected by combining a decoding result of the previous round of iterative decoding and the channel input of the previous round of iterative decoding, so as to obtain corrected coded bit soft information.
It can be understood that the conventional decoding algorithm of the LDPC code is a soft information message passing iterative decoding algorithm, and the channel parameter estimation error directly causes the linear scale change of the encoded bit soft information llr_ch, and meanwhile, the non-optimal constellation demapping algorithm or the detection algorithm also affects the scale change of the encoded bit soft information llr_ch, so that in the case of the channel estimation error, the encoded bit soft information llr_ch input by the channel needs to be linearly corrected.
In the actual execution process, the embodiment of the application can receive the channel input LLR_ch_cur of the iterative decoding of the current round, the decoding result of the iterative decoding of the LDPC of the previous round and the channel input LLR_ch_pre of the iterative decoding of the previous round, and correct the channel input of the iterative decoding of the current round by utilizing a correction method, such as a front correction method and a loop correction method, so as to obtain corrected coded bit soft information, thereby ensuring the accuracy of the correction result.
Optionally, in one embodiment of the present application, before receiving the channel input of the current round of iterative decoding, the method further includes: initializing the correction parameters of the log likelihood ratio, the working points of the iterative decoder of the low density parity check code and the loop self-adaptive correction parameters.
As a possible implementation manner, the embodiment of the application may initialize the log-likelihood ratio correction parameter α, the operating point of the low-density parity-check code iterative decoder, and the loop adaptive correction parameter before performing the soft information correction of the code bits, and may also initialize the average mutual information AMI of the code bits after the previous round of correction by using the operating point of the low-density parity-check code iterative decoder according to different methods when adjusting the log-likelihood ratio correction parameter subsequently est Coding bit average mutual information AMI of previous prediction pre And laying a data foundation for adjusting the log likelihood ratio correction parameters by using a loop correction method.
Optionally, in one embodiment of the present application, correcting the channel input of the current round of iterative decoding includes: adjusting the correction parameters of the log likelihood ratio by using a preset forward correction method or a loop correction method; and correcting the channel input of the iterative decoding of the current round by using the log-likelihood ratio correction parameters to obtain corrected coded bit soft information.
Further, in the embodiment of the present application, a forward correction method or a loop correction method may be used to adjust a log-likelihood ratio correction parameter α, and correct a channel input llr_ch_cur of iterative decoding of a current round by using the log-likelihood ratio correction parameter α to obtain corrected code bit soft information llr_ch_adj, where a correction formula may be:
LLR_ch_adj＝α×LLR_ch_cur。
optionally, in an embodiment of the present application, adjusting the log likelihood ratio correction parameter using a forward correction method includes: and calculating to obtain the log-likelihood ratio correction parameter of the current round iteration by combining the working point of the low-density parity check code iterative decoder with the channel input of the current round iterative decoding.
In some embodiments, the embodiment of the present application may adjust the log-likelihood ratio correction parameter a by using a forward correction method, and directly calculate the channel input llr_ch_cur of the current round of iterative decoding by combining the working point of the low-density parity-check code iterative decoder, so as to obtain the log-likelihood ratio correction parameter a of the current round of iterative decoding.
Optionally, in one embodiment of the present application, adjusting the log likelihood ratio correction parameter using a loop correction method includes: combining the decoding result of the previous iteration decoding and the channel input of the previous iteration decoding, and calculating to obtain the average mutual information of the coded bits after the previous iteration correction; calculating the difference between the average mutual information of the coded bits after the previous round correction and the average mutual information of the coded bits predicted in the previous round, and adjusting the log-likelihood ratio correction parameters by combining the difference and the loop self-adaptive correction parameters.
In other embodiments, the embodiments of the present application may adjust the log-likelihood ratio correction parameters by using a loop correction method, and calculate the average mutual information AMI of the encoded bits after the previous round of correction by using the decoding result of the previous round of LDPC iterative decoding and combining the channel input llr_ch_pre of the previous round of iterative decoding est And by comparing the code bit average mutual information AMI after the previous round correction est And the coded bit average mutual information AMI of the previous round of prediction pre According to AMI est And AMI pre The log-likelihood ratio correction parameter alpha is adjusted by combining the loop adaptive correction parameter, wherein the embodiment of the application can initialize or update the code bit average mutual information AMI after the last round of correction by utilizing the working point of the low-density parity check code iterative decoder est And the coded bit average mutual information AMI of the previous round of prediction pre 。
In step S102, based on the corrected soft information of the encoded bits, the average mutual information of the encoded bits of the current round prediction is obtained, and based on the average mutual information of the encoded bits of the current round prediction, the decoding results of the encoded bits of the current round prediction in decoding modes with different complexity are predicted, corresponding decoding options are determined, and corresponding decoding option control signals are output.
In the actual implementation process, the embodiment of the application can receive the corrected code bit soft information LLR_ch_adj, so as to obtain the code bit average mutual information AMI of the current round prediction by utilizing the corrected code bit soft information LLR_ch_adj cur Average mutual information AMI with coded bits according to the prediction of the present round cur The method has the advantages that the decoding results of the decoding modes with different complexity are predicted, the decoding options are determined, the corresponding decoding option control signals mode are output, and compared with the traditional method for predicting the decoding performance by using the channel parameter SNR and the channel state information CSI, the method can realize accurate prediction of the decoding performance results of the decoding modes with different complexity, and is beneficial to adaptively selecting the decoding options.
Optionally, in one embodiment of the present application, predicting the decoding result of the different complexity decoding modes based on the coded bit average mutual information of the current round prediction and determining the decoding options includes: combining the average mutual information of the coding bits of the current round prediction with the error bit rate or the error block rate performance curve of the coding bit average mutual information under the different complexity decoding modes to obtain the error bit rate or the error block rate performance prediction result of the different complexity decoding modes under the average mutual information of the coding bits of the current round prediction; and screening a decoding mode which meets the preset performance condition and has the lowest decoding complexity from the decoding modes with different complexity based on the bit error rate or the block error rate performance prediction result to serve as a determined decoding option, and selecting non-decoding as the determined decoding option when all the decoding modes do not meet the preset performance condition.
As a possible implementation manner, the embodiment of the present application may predict the coding bit average mutual information AMI according to the current round cur Combining the average mutual information of the coding bits under different complexity decoding modes with the performance curve of bit error rate or block error rate (AMI-BER/BLER) to obtain the average mutual information of the coding bits AMI of the current round prediction cur And selecting BER or BLER performance prediction results of decoding modes with different complexity to meet the current bit error rate or block error rate performance requirement, selecting the decoding mode with the lowest complexity, if the BER or BLER performance prediction results of all the selectable decoding modes do not meet the current bit error rate or block error rate performance requirement, predicting decoding failure, selecting a non-decoding option, and guiding retransmission by using the prediction results to perform next round of decoding.
In step S103, a corresponding decoding mode is selected according to the decoding option control signal, so that the corrected encoded bit soft information is iteratively decoded in the corresponding decoding mode, and a final decoding result is obtained.
In some embodiments, the embodiments of the present application may select a corresponding decoding mode according to the decoding option control signal mode, perform LDPC iterative decoding on the modified encoded bit soft information llr_ch_adj, and output a decoding result, where when predictive decoding fails, the embodiments of the present application do not perform LDPC iterative decoding.
Further, the embodiment of the application may update the channel input llr_ch_pre of the previous iteration decoding by using the channel input llr_ch_cur of the current iteration decoding, and use the coded bit average mutual information AMI of the current iteration prediction cur Updating the coding bit average mutual information AMI of the previous round of prediction pre And the channel input of the iterative decoding of the next round is corrected, and the log-likelihood ratio correction parameters are adjusted, so that the loop self-adaptive correction of the channel parameter estimation errors is realized.
Through self-adaptive selection of proper decoding options, the embodiment of the application can give consideration to the decoding complexity and throughput rate of the decoder under different channel quality, enhance the adaptability of the decoder to channel quality change, reduce the decoding resource waste caused by decoding failure and improve the decoding efficiency.
The working principle of the adaptive LDPC iterative decoding method according to the embodiments of the present application will be described in detail with reference to fig. 2 to 5 in a plurality of embodiments.
Embodiment one (utilizing Forward correction method)
As shown in fig. 2, the embodiment of the present application may use a forward correction method to input llr_ch_cur to the channel iteratively decoded in the current round i Correcting to obtain corrected code bit soft information LLR_ch_adj i Soft information LLR_ch_adj using corrected code bits i BERBER or BLER performance predictions for SPA and AQNMSA are obtained, with SPA selected for use, AQNMSA selected for use, or no decoding.
Specifically, as shown in fig. 3, an embodiment of the present application may include the following steps:
step S301: initializing log-likelihood ratio correction parameter alpha and working point AMI of low-density parity-check code iterative decoder t 。
Step S302: receiving channel input LLR_ch_cur of current round iterative decoding i By using the forward correction method,adjusting a log likelihood ratio correction parameter alpha; channel input LLR_ch_cur for iterative decoding of current round using log likelihood ratio correction parameter alpha i Correcting to obtain corrected code bit soft information LLR_ch_adj i The correction formula may be:
LLR_ch_adj i ＝α×LLR_ch_cur i ，
where i=1, 2, …, N is the LDPC code bit length, i.e. code length.
When the forward correction method is used to adjust the log-likelihood ratio correction parameter α, the embodiment of the present application may use the channel input llr_ch_cur of the current round of iterative decoding, and combine the working point channel capacity C of the low-density parity-check code iterative decoder t Solving the following equation to obtain the log likelihood ratio correction parameter alpha of the current round iteration:
where h9·) is a binary entropy function.
Step S303: the embodiment of the application can receive the corrected code bit soft information LLR_ch_adj i And uses the corrected code bit soft information LLR_ch_adj i Obtaining coding bit average mutual information AMI of current round prediction cur The formula may be:
wherein h (·) is a binary entropy function.
The embodiment of the application can predict the coding bit average mutual information AMI according to the current round cur And predicting BER or BLER performance prediction results of the SPA and the AQNMSA in two decoding modes, selecting to use the SPA, using the AQNMSA or not decoding, and outputting a corresponding decoding option control signal mode.
The SPA has good decoding threshold performance, but high decoding complexity and is sensitive to channel parameter estimation errors; the AQNMSA has low decoding complexity and good robustness, the robustness of the AQNMSA decoding mode is utilized, the decoding performance can be ensured not to be remarkably deteriorated under the condition of channel parameter estimation errors, the decoding result can be directly used for the accurate estimation of AMI, but the decoding threshold performance is inferior to SPA, and the method further comprises the option of non-decoding.
Step S304: receiving the corrected coded bit soft information LLR_ch_adj of step S302 i According to the decoding option control signal mode of step S303, a corresponding decoding mode is selected, and the corrected coded bit soft information llr_ch_adj is decoded i Performing LDPC iterative decoding, outputting decoding results of current round iterative decoding, or predicting decoding failure, and not performing LDPC iterative decoding; step S302 is skipped.
Embodiment two (using Loop adaptive correction method)
As shown in fig. 4, the embodiment of the present application may use a loop adaptive correction method to iteratively decode the channel input llr_ch_cur for the current round i Correcting to obtain corrected code bit soft information LLR_ch_adj i Soft information LLR_ch_adj using corrected code bits i BER performance prediction results of SPA and AQNMSA are obtained, SPA is selected to be used, AQNMSA is used or decoding is not performed.
Specifically, as shown in fig. 5, an embodiment of the present application may include the following steps:
step S501: initializing log-likelihood ratio correction parameter alpha and working point AMI of low-density parity-check code iterative decoder t Simultaneously initializing preset loop self-adaptive correction parameters, and iterating the working point AMI of the decoder by using the low-density parity-check code t Initializing coding bit average mutual information AMI after previous round correction est Coded bit average mutual information AMI of previous round prediction pre 。
Step S502: receiving channel input LLR_ch_cur of current round iterative decoding i Decoding result of iterative decoding of previous round and channel input LLR_ch_pre of iterative decoding of previous round i Adjusting the log likelihood ratio correction parameter alpha by using a loop self-adaptive correction methodChannel input LLR_ch_cur for iterative decoding of current round i Correcting to obtain corrected code bit soft information LLR_ch_adj i The correction formula may be:
LLR_ch_adj i ＝α×LLR_ch_cur i ，
where i=1, 2, …, N is the LDPC code bit length, i.e. code length.
When the embodiment of the application adjusts the log likelihood ratio correction parameter α by using the loop correction method, the decoding result of the previous round of LDPC iterative decoding can be used to combine the channel input LLR_ch_pre of the previous round of iterative decoding i Obtaining conditional probability distribution PDF when the coded bit c=0 of the previous iteration decoding c＝0 (llr_ch_pre) and conditional probability distribution PDF when coded bit c=1 c＝1 (LLR_ch_pre) further calculates the average mutual information AMI of the coded bits after the previous round of correction est The formula may be:
The embodiment of the application can compare the average mutual information AMI of the code bits after the last round of correction est And the coded bit average mutual information AMI of the previous round of prediction pre According to preset loop self-adaptive correction parameters and AMI est And AMI pre To correct the log-likelihood ratio correction parameter a.
Step S503: receiving corrected code bit soft information LLR_ch_adj i Soft information LLR_ch_adj using corrected code bits i Obtaining coding bit average mutual information AMI of current round prediction cur The formula may be:
wherein, h (·) is a binary entropy function, AMI in practical application cur The calculation of (2) can be performed with low complexityA degree approximation algorithm.
The embodiment of the application can predict the coding bit average mutual information AMI according to the current round cur And predicting BER performance prediction results of the SPA and the AQNMSA in two decoding modes, selecting to use the SPA, using the AQNMSA or not decoding, and outputting a corresponding decoding option control signal mode.
Step S504: soft information LLR_ch_adj based on modified code bits i And a decoding option control signal mode for selecting a corresponding decoding mode and correcting the corrected code bit soft information LLR_ch_adj i And performing LDPC iterative decoding, outputting a decoding result of the current round iterative decoding, or predicting decoding failure, and not performing LDPC iterative decoding.
Step S505: channel input LLR_ch_cur using current round iterative decoding i Updating the channel input LLR_ch_pre of the previous iteration decoding i Coded bit average mutual information AMI using current round prediction cur Updating the coded bit-averaged mutual information aMI of the previous run prediction pre Updating the decoding result of the previous round of iterative decoding by using the decoding result of the current round of iterative decoding, and skipping to step S502.
According to the self-adaptive LDPC iterative decoding method provided by the embodiment of the application, the decoding result of the previous round of iterative decoding and the channel input of the previous round of iterative decoding can be combined, the channel input of the current round of iterative decoding is corrected, the corrected coded bit soft information is obtained, the accurate prediction of the decoding performance results of different complexity decoding modes can be realized, the decoding options are adaptively selected, the coded bit average mutual information of the current round of prediction is obtained through the corrected coded bit soft information, the decoding results in the different complexity decoding modes are predicted, the corresponding decoding options are determined, the control signals of the corresponding decoding options are output, the corrected coded bit soft information is subjected to iterative decoding in the corresponding decoding modes, the final decoding result is obtained, the decoding complexity and throughput rate of the decoder in different channel quality can be considered, the adaptability of the decoder to channel quality change is enhanced, meanwhile, the decoding resource waste caused by decoding failure is reduced, the decoding efficiency is improved, and the accuracy and the reliability of the decoding results are ensured. Therefore, the technical problems that in the related art, the decoding performance of a plurality of decoding modes is difficult to accurately predict, the prediction result is influenced, the comprehensive performance of the decoding modes is poor, the performance of the selectable decoding modes is greatly limited, the effective correction of channel parameter estimation errors is lacking, the actual decoding performance is reduced, the decoding efficiency is reduced and the like are solved.
Next, an adaptive LDPC iterative decoding apparatus according to an embodiment of the present application will be described with reference to the accompanying drawings.
Fig. 6 is a block schematic diagram of an adaptive LDPC iterative decoding apparatus according to an embodiment of the present application.
As shown in fig. 6, the adaptive LDPC iterative decoding apparatus 10 is applied to a low density parity check code iterative decoder, wherein the apparatus 10 includes: initialization module 100, correction module 200, prediction module 300, and coding module 400.
Specifically, the initialization module 100 is configured to initialize the log-likelihood ratio correction parameter, the operating point of the low-density parity-check code iterative decoder, and the loop adaptive correction parameter.
The correction module 200 is configured to receive a channel input of the current round of iterative decoding, and correct the channel input of the current round of iterative decoding by combining a decoding result of the previous round of iterative decoding and the channel input of the previous round of iterative decoding, so as to obtain corrected coded bit soft information.
The prediction module 300 is configured to obtain coded bit average mutual information of current round prediction based on the modified coded bit soft information, predict a decoding result under different complexity decoding modes based on the coded bit average mutual information of current round prediction, determine a corresponding decoding option, and output a corresponding decoding option control signal.
The decoding module 400 is configured to select a corresponding decoding mode according to the decoding option control signal, so as to perform iterative decoding on the modified encoded bit soft information in the corresponding decoding mode, thereby obtaining a final decoding result.
Optionally, in one embodiment of the present application, the correction module 200 includes: an adjusting unit and a correcting unit.
The adjusting unit is used for adjusting the log likelihood ratio correction parameters by using a preset forward correction method or a loop correction method.
And the correction unit is used for correcting the channel input of the current round of iterative decoding by utilizing the log-likelihood ratio correction parameters to obtain corrected code bit soft information.
Optionally, in one embodiment of the present application, the adjusting unit includes: a first adjustment subunit.
The first adjusting subunit is configured to calculate, by using the working point of the low-density parity check code iterative decoder and combining with the channel input of the current round iterative decoding, a log-likelihood ratio correction parameter of the current round iterative.
Optionally, in one embodiment of the present application, the adjusting unit further includes: a calculation subunit and a second adjustment subunit.
The computing subunit is configured to combine the decoding result of the previous iteration decoding with the channel input of the previous iteration decoding, and compute to obtain the average mutual information of the coded bits after the previous iteration correction.
And the second adjusting subunit is used for calculating the difference value between the coded bit average mutual information after the previous round of correction and the coded bit average mutual information predicted by the previous round of correction, and adjusting the log likelihood ratio correction parameter by combining the difference value and the loop self-adaptive correction parameter.
Optionally, in one embodiment of the present application, the prediction module 300 includes: a prediction unit and a screening unit.
The prediction unit is used for combining the average mutual information of the coding bits of the current round prediction and the average mutual information of the coding bits under different complexity decoding modes, namely the bit error rate or the block error rate performance curve, so as to obtain the bit error rate or the block error rate performance prediction result of the decoding modes with different complexity under the average mutual information of the coding bits of the current round prediction.
And the screening unit is used for screening a decoding mode which meets the preset performance condition and has the lowest decoding complexity from the decoding modes with different complexity based on the bit error rate or block error rate performance prediction result to serve as a determined decoding option, and selecting non-decoding as the determined decoding option when all the decoding modes do not meet the preset performance condition.
It should be noted that the foregoing explanation of the embodiment of the adaptive LDPC iterative decoding method is also applicable to the adaptive LDPC iterative decoding apparatus of this embodiment, and will not be repeated herein.
According to the self-adaptive LDPC iterative decoding device provided by the embodiment of the application, the decoding result of the previous round of iterative decoding and the channel input of the previous round of iterative decoding can be combined, the channel input of the current round of iterative decoding is corrected, the corrected coded bit soft information is obtained, the accurate prediction of the decoding performance results of different complexity decoding modes can be realized, the decoding options are adaptively selected, the coded bit average mutual information of the current round of prediction is obtained through the corrected coded bit soft information, the decoding results under the different complexity decoding modes are predicted, the corresponding decoding options are determined, the corresponding decoding option control signals are output, the corrected coded bit soft information is subjected to iterative decoding under the corresponding decoding modes, the final decoding result is obtained, the decoding complexity and throughput rate of the decoder under different channel quality can be considered, the adaptability of the decoder to channel quality change is enhanced, meanwhile, the decoding resource waste caused by decoding failure is reduced, the decoding efficiency is improved, and the accuracy and the reliability of the decoding results are ensured. Therefore, the technical problems that in the related art, the decoding performance of a plurality of decoding modes is difficult to accurately predict, the prediction result is influenced, the comprehensive performance of the decoding modes is poor, the performance of the selectable decoding modes is greatly limited, the effective correction of channel parameter estimation errors is lacking, the actual decoding performance is reduced, the decoding efficiency is reduced and the like are solved.
Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device may include:
The processor 702 implements the adaptive LDPC iterative decoding method provided in the above embodiment when executing a program.
Further, the electronic device further includes:
a communication interface 703 for communication between the memory 701 and the processor 702.
The memory 701 may include a high-speed RAM memory or may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory.
If the memory 701, the processor 702, and the communication interface 703 are implemented independently, the communication interface 703, the memory 701, and the processor 702 may be connected to each other through a bus and perform communication with each other. The bus may be an industry standard architecture (Industry Standard Architecture, abbreviated ISA) bus, an external device interconnect (Peripheral Component, abbreviated PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, abbreviated EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, only one thick line is shown in fig. 7, but not only one bus or one type of bus.
Alternatively, in a specific implementation, if the memory 701, the processor 702, and the communication interface 703 are integrated on a chip, the memory 701, the processor 702, and the communication interface 703 may communicate with each other through internal interfaces.
The processor 702 may be a central processing unit (Central Processing Unit, abbreviated as CPU) or an application specific integrated circuit (Application Specific Integrated Circuit, abbreviated as ASIC) or one or more integrated circuits configured to implement embodiments of the present application.
The present embodiment also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the adaptive LDPC iterative decoding method as above.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless explicitly defined otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and additional implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order from that shown or discussed, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or N wires, a portable computer cartridge (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As with the other embodiments, if implemented in hardware, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.
The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like. Although embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.
Claims (11)
1. An adaptive LDPC iterative decoding method, applied to a low density parity check code iterative decoder, wherein the method comprises the steps of:
receiving channel input of current round iterative decoding, and correcting the channel input of the current round iterative decoding by combining a decoding result of the previous round iterative decoding and the channel input of the previous round iterative decoding to obtain corrected coded bit soft information;
obtaining coding bit average mutual information of current round prediction based on the corrected coding bit soft information, predicting decoding results under different complexity decoding modes based on the coding bit average mutual information of the current round prediction, determining corresponding decoding options, and outputting corresponding decoding option control signals;
And selecting a corresponding decoding mode according to the decoding option control signal, so as to perform iterative decoding on the corrected coded bit soft information under the corresponding decoding mode, and obtaining a final decoding result.
2. The method of claim 1, further comprising, prior to receiving the channel input for the current round of iterative decoding:
initializing a log-likelihood ratio correction parameter, a working point of the low-density parity-check code iterative decoder and a loop self-adaptive correction parameter.
3. The method of claim 2, wherein said modifying the channel input of the current round of iterative decoding comprises:
adjusting the log likelihood ratio correction parameters by using a preset forward correction method or a loop correction method;
and correcting the channel input of the current round of iterative decoding by using the log-likelihood ratio correction parameters to obtain the corrected coded bit soft information.
4. A method according to claim 3, wherein said adjusting said log likelihood ratio correction parameter using a forward correction method comprises:
and calculating the log likelihood ratio correction parameter of the current round iteration by using the working point of the low-density parity check code iterative decoder and combining the channel input of the current round iterative decoding.
5. A method according to claim 3, wherein said adjusting said log likelihood ratio correction parameter using a loop correction method comprises:
combining the decoding result of the previous iteration decoding and the channel input of the previous iteration decoding, and calculating to obtain the average mutual information of the coded bits after the previous iteration correction;
and calculating a difference value between the coded bit average mutual information corrected in the previous round and the coded bit average mutual information predicted in the previous round, and adjusting the log likelihood ratio correction parameter by combining the difference value and the loop self-adaptive correction parameter.
6. The method of claim 2, wherein predicting the decoding results of different complexity decoding modes based on the current round predicted coded bit-averaged mutual information and determining a decoding option comprises:
combining the average mutual information of the coding bits of the current round prediction with the error bit rate or the error block rate performance curve of the coding bit average mutual information under different complexity decoding modes to obtain the error bit rate or the error block rate performance prediction result of the different complexity decoding modes under the average mutual information of the coding bits of the current round prediction;
And screening a decoding mode which meets a preset performance condition and has the lowest decoding complexity from the decoding modes with different complexity based on the bit error rate or block error rate performance prediction result to serve as a determined decoding option, and selecting non-decoding as the determined decoding option when all the decoding modes do not meet the preset performance condition.
7. An adaptive LDPC iterative decoding apparatus applied to a low density parity check code iterative decoder, wherein the apparatus comprises:
the initialization module is used for initializing the log-likelihood ratio correction parameters, the working points of the low-density parity check code iterative decoder and the loop self-adaptive correction parameters;
the correction module is used for receiving the channel input of the current round of iterative decoding, and correcting the channel input of the current round of iterative decoding by combining the decoding result of the previous round of iterative decoding and the channel input of the previous round of iterative decoding to obtain corrected code bit soft information;
the prediction module is used for obtaining the coding bit average mutual information of the current round prediction based on the corrected coding bit soft information, predicting the decoding results of the current round prediction in different complexity decoding modes based on the coding bit average mutual information of the current round prediction, determining corresponding decoding options and outputting corresponding decoding option control signals;
And the decoding module is used for selecting a corresponding decoding mode according to the decoding option control signal so as to carry out iterative decoding on the corrected coded bit soft information under the corresponding decoding mode to obtain a final decoding result.
8. The apparatus of claim 7, wherein the correction module comprises:
the adjusting unit is used for adjusting the log likelihood ratio correction parameters by using a preset forward correction method or a loop correction method;
and the correction unit is used for correcting the channel input of the current round of iterative decoding by utilizing the log-likelihood ratio correction parameter to obtain the corrected code bit soft information.
9. The apparatus according to claim 8, wherein the adjusting unit comprises:
and the first adjusting subunit is used for calculating the log likelihood ratio correction parameter of the current round iteration by utilizing the working point of the low-density parity check code iterative decoder and combining the channel input of the current round iterative decoding.
10. The apparatus of claim 8, wherein the adjustment unit further comprises:
a calculating subunit, configured to combine the decoding result of the previous iteration decoding with the channel input of the previous iteration decoding, and calculate to obtain the average mutual information of the coded bits after the previous iteration correction;
And the second adjusting subunit is used for calculating the difference value between the coded bit average mutual information after the last round of correction and the coded bit average mutual information predicted by the last round of correction, and adjusting the log likelihood ratio correction parameter by combining the difference value and the loop self-adaptive correction parameter.
11. The apparatus of claim 7, wherein the prediction module comprises:
the prediction unit is used for combining the coding bit average mutual information of the current round prediction and the coding bit average mutual information-bit error rate or block error rate performance curve under different complexity decoding modes to obtain a bit error rate or block error rate performance prediction result of the different complexity decoding modes under the coding bit average mutual information of the current round prediction;
and the screening unit is used for screening a decoding mode which meets a preset performance condition and has the lowest decoding complexity from the decoding modes with different complexity based on the bit error rate or block error rate performance prediction result to serve as a determined decoding option, and selecting non-decoding as the determined decoding option when all the decoding modes do not meet the preset performance condition.
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